Research On Energy Allocation And Resource Scheduling Technologies In SWIPT Network

Simultaneous wireless information and power transfer(SWIPT)is information and energy cooperative transmission technology that is applied in energy-constrained networks.Different from traditional networks that rely on external power supply,SWIPT network nodes collect energy from the received RF signals and use them for subsequent information transmission,which overcomes the dependence on external power supplies for energy harvesting.At the same time,the inconvenience for wireless node to configure reliable power supply has also been compensated.In the SWIPT network,reasonable resource allocation and scheduling plays an important role in the improvement of information transmission rate and energy harvesting capability for SWIPT network nodes.This dissertation studies orthogonal frequency division multiplexing(OFDM)-based energy allocation and resource(subcarrier,power,bit)scheduling schemes in SWIPT network.Specific researches are provided as below.Aiming at the resource allocation problem in virtual full-duplex SWIPT network,optimal buffer-aided SWIPT relay selection and joint subcarrier and energy allocation strategies are investigated in chapter 2.Firstly,mathematical model is constructed with the reference of water-filling factor aided search algorithm.With the target of energy-efficiency maximization,the proposed scheme solves optimal problem to select the best SWIPT forward relay with the consideration of multiple constraint conditions such as energy,information transmission rate,as well as the interference of the best receive relay.The optimal solution of subcarrier energy allocation for the best SWIPT forward relay is obtained.Simulation results shows that,compared to the joint resource allocation algorithm that aims to maximize end-to-end achievable rate,the proposed strategy reduces SWIPT inter-relay interference and guarantees higher energy efficiency with larger transmit power at source.In chapter 3,multiuser joint subcarrier and bit allocation scheme is proposed in SWIPT network with transmission rate constraint.Based on marginal adaptation(MA)criterion,the proposed scheme considers source transmission power minimization as its optimal objective,which is subject to SWIPT user energy restriction,transmission rate(bit)constraint and SWIPT user rate fairness ratio.Firstly,subcarrier allocation is performed with the guarantee of SWIPT user rate fairness.Secondly,Hughes-Hartogs(HH)bit allocation algorithm is performed twice in order to obtain the transmission bit numbers in each SWIPT user subcarriers.Simulation results reveal the relationships between the assigned bits,SWIPT power splitting factor and source transmission power.The effect of energy conversion efficiency to energy-efficiency(EE)is also presented.Simulation results indicate that,the proposed scheme effectively reduces source transmission power with the comparison of average bit allocation scheme in the same available allocated bit scenario.Moreover,through the selection of appropriate SWIPT users,the proposed scheme achieves the maximum EE in SWIPT network.In chapter 4,multiuser joint subcarrier and power allocation scheme is investigated in SWIPT network with source transmission power constraint.Based on rate adaptation(RA)criterion,the proposed scheme considers information transmission rate maximization as the optimal objective,with the constraint conditions such as SWIPT user energy threshold,source transmission power,etc.Firstly,subcarrier allocation is performed for each SWIPT user.Secondly,subcarrier,power and power splitting factor is jointly optimized in order to obtain the optimal solution of information transmission rate.Simulation results reveal the relationships between source transmission power,energy harvesting threshold and information transmission rate.This dissertation initially studies OFDM-based energy allocation and multi-node multi-resource scheduling technologies in SWIPT network.Research achievements provide significant value for the further related works.